Video Annotation And Its Different Types
Video annotation is essential to improve the performance of many AI-based models and projects. Video annotation helps in achieving correct datasets to train machines and different models. In this blog post, we have talked about what is video annotation and how different types of video annotation techniques can benefit various organizations and businesses.
What is Video Annotation?
Video annotation is a process in which the content of a video is tagged and labeled to create annotated video data to train machines efficiently. Nowadays many companies prefer to annotate videos and achieve high-quality datasets for projects based on machine learning and artificial intelligence. Video annotation is a process conducted by humans in the workplace but with the advancement in technology. During the process, annotators use several tools to achieve accurate results.
What is the Usage of Annotating Videos
The most important usage of video annotation is to create datasets that can help the machines identify objects and things. Nowadays, various ongoing and upcoming projects are based on machine learning and AI models which require artificial learning. Video annotation helps such models learn quickly and efficiently by creating datasets from the video footage.
Following are the few use cases where video annotation has played a significant role in achieving the desired results:
1. In Machine Learning-Based Projects & Models
The best use case of video annotation is to train machine learning models. The manufacturing industry has recognized the capability of video annotation in preparing data sets and has understood their effectiveness in training machines. Human annotators are experts in labeling the video footage and deriving data that help the machines achieve the desired results by gradually learning things.
2. In Healthcare Industry
The video annotation technique is nowadays used efficiently by medical facilities owners. In medical facilities, different types of videos such as ultrasound videos are annotated to attract the attention of the students to different parts of the body. Video tagging in the medical industry helps the students get a close view of the organs and provides efficient learning.
3. In Education Industry
Video annotation has shown great results in the education industry. In colleges and universities, videos are annotated to offer an advanced and innovative way of learning. For eg: Teachers and students annotate videos on the learning management system to create and share notes. Video annotation in the learning management system is also used to identify and analyze different parts of the course materials.
4. In Compliance & Redaction workflows
Videos are annotated by professionals in law enforcement and legal teams. Video tagging is mostly done in the law enforcement department whenever there is a need to blur a specific piece of evidence from a video. This sensitive information can be anything from a person’s face to the footage. Video annotation is used in regulatory compliance of standard rules and guidelines are followed on the broadcast network or internet.
5. In Retail Sector
Nowadays, video annotation is widely used in the retail sector. Both online and offline retail shop owners are using the technique to manage their product inventory and provide a good shopping experience to the customers. Also, video annotation is used to analyze and track the customer’s buying patterns when they shop at a retail outlet. Using video annotation techniques, professionals can find out a price tag of a specific product or can know whether a product is in stock or not.
Video Annotations Types
There are different video annotation methods available that human annotators can opt for to create datasets as per their business requirements. Sometimes, the types of video annotations used to create datasets are decided by the enterprises and organizations. Overall, there are five different types of video annotations methods that you can use to create the required datasets and these are 2D bounding boxes, 3D cuboids, landmarks, polylines, and polygons.
Here we will discuss each one of the video annotations types in detail:
1. 2D Bounding Boxes
In the 2D bounding boxes annotation type, the annotator needs to identify, categorize and label the objects using rectangle-shaped boxes. To annotate the videos with this method, the annotator needs to draw rectangular boxes around the required objects in motion across several frames. To ensure that the objects are labeled and categorized correctly, the annotator should draw the rectangular boxes close to all the edges of the required object.
2. 3D Bounding Boxes
3D bounding boxes video annotation type is used when the annotator wants to depict the item realistically. With the 3D bounding boxes method, the annotator can know about various characteristics of the required object in detail including length, breadth, and the estimated depth. Also, all kinds of objects can be detected using this methodology to create the required datasets.
Polygons are used for annotating videos when both 2D and 3D bounding boxes are not capable of determining the characteristics and form of a movable object. To create high-quality datasets from a video, it is mandatory to know the details of the moving objects, and this is where polygons come in. Polygons are popular to depict a movable object with higher accuracy and are, therefore, the choice of most annotators. While using polygons for annotating videos, annotators need to place the dots around the edges and border of the object to create lines.
4. Landmark or Key-point
Landmark and keypoint annotation is used by many organizations these days. In such a type of annotation technique, annotators need to generate the dots for a given image. After the dots are generated, the annotators build the structure of the required objects by connecting and linking the dots. Such type of annotation is used to identify and analyze even the minute details of objects, postures, and shapes.
5. Lines and Splines
Lines and splines annotation is most used by professionals in the autonomous driving sector. Human annotators use this annotation type to make the robots learn about lanes and borders. The annotators start by drawing lines between the locations which help machines to differentiate between the lanes and borders gradually and make the correct decisions in real-life scenarios.
Performing video annotation can be challenging at times if you don’t have the access to the correct tools, and technology. Also, annotating videos can be boring and time-taking that can hinder you from focusing on important business activities. You can outsource video annotation services to the experts to achieve excellent results and save time and money.
SunTec.AI is your best bet when it comes to video annotation services. With an in-house team of video annotators on board, we can customize our services to fulfill your business requirements. From bounding boxes to semantic segmentation, polygon annotation, or key-point annotation, we have all the skills, technical expertise, and experience to offer you out-of-the-box services. Find out more about why your enterprise should outsource video annotation services to SunTec.AI.
1. Why video annotation is useful in machine learning?
Annotating videos helps the machines in getting a better understanding of the texts and visuals. If you annotate a video to create datasets you will be able to deliver a good understanding of videos to the machines, which help them make the decisions in real-life events. All in all, video annotation helps machines learn and recall key information efficiently.
2. What are the steps that you can follow to annotate videos well?
Following are the few steps that you should keep in mind if you are annotating videos manually:
- Start with a pencil or a pen in your hand.
- Now visualize all the information in the video and read carefully if there are any texts in the video.
- If you are watching the video for the first time, try giving it more time and understand what it is about and what are the important objects in the video.
- After you have developed a good understanding of the video you can start annotating it.
3. If I outsource my video annotation work will my data be safe?
Yes, if you outsource your video annotation work to the premium and renowned service providers there will be no risk to your data. Professional video annotation companies like SunTec.AI follow various standards and guidelines to handle your crucial data safely. Also, professional service providers have experts in their teams that have signed NDAs with the company to add extra security to the process.
4. Why is outsourcing video annotating to service providers beneficial?
Outsourcing your video annotation work to the service providers come with many benefits. The major benefit is that you get assistance from professional video annotators that hold expertise in annotating videos and achieving 100% accurate datasets. You can use these high-quality datasets to train your machines and create AI-based projects that are capable of delivering expected results. Also, by outsourcing the project to renowned service providers, you can get a quick turnaround time.